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Parallel algorithms are problematic to develop because of the negative influence of synchronisation, complicated behaviour of threads’ capturing computing resources. Experimental results show perfo...

Accurately modeling memory timing in a processor simulator is crucial for obtaining accurate and useful performance predictions. DRAM has a complex timing and reordering scheme, which results in highly varying access latencies depending on the type of operations, address stream patterns and bandwidth load. Therefore, DRAM simulators model the DRAM timings as a clocked state machine. However, some processor simulators, in particular loosely synchronized parallel simulators, assume an immediate-response memory model, requesting an immediate estimation of the memory latency. In this letter, we discuss the modeling issues in transforming a state machine DRAM simulator into an immediate-response simulator, which can be directly plugged into a processor simulator supporting an immediate-response memory model and/or a relaxed parallel simulation model. We show that the adapted model is accurate within 2 percent compared to the state machine simulator.

In simulations, when using multipartitioned computers, the way in which the mesh is partitioned directly affects the average time per iteration, and therefore, the computational cost. This study proposes an analysis of the average time per iteration of 23 different partition methods available for tridimensional mesh in software FLUENT 19.2. For the calculation of the average iteration time, 100 iterations were used. Generally, the best partitioning methods were those in which the mesh division was made perpendicularly to the axis of the equipment. It was stated the choice of an adequate partitioning method can save high costs of computational power. For the hydrocyclone studied, with a computer with 8 cores, approximately 24.56 hours of simulation were saved, representing almost 20% of the total time. En simulaciones con computadoras multi-particionadas, la forma con que la malla es fraccionada afecta el tiempo promedio por iteración y el costo computacional. En este trabajo, se analiza el tiempo promedio por iteración de los 23 métodos de fraccionamiento disponibles para mallas tridimensionales del software FLUENT 19.2. Se realizaron 100 iteraciones para la determinación del tiempo promedio por iteración. En general, los mejores métodos de fraccionamiento fueron aquellos en donde la división de la malla fue hecha perpendicularmente al eje en el cual el equipo se encontraba direccionado. En la simulación de un hidrociclón, mediante el uso de una computadora de 8 núcleos, se logró ahorrar aproximadamente 24.56 horas, lo que significó casi el 20% del tiempo total. De esta manera, la adecuada selección fraccionamiento, puede constituir un gran ahorro del costo computacional.

The Monte Carlo algorithm has been extensively used for photon transport simulations in medical imaging to assists doctors in Photodynamic Therapy for treatment of wide range of medical conditions including varieties of cancer by eliciting phototoxicity in cells. Previously this was done using static 2 Dimensional models on traditional CPUs. With the advent of GPU Computing further work was done to extend this model by separating the PRNG.

The objectives of this study are to develop (a) the Julia Flow and Transport Simulator (JFTS), a serial and parallel, high performance non-isothermal, multi-phase, multi-component general simulator of flow and transport through porous/fractured media, and (b) an associated module that describes quantitatively the Equation-of-State (EOS) of the complete H2O+CH4 system by covering all combinations of phase coexistence that are possible in geologic media and including all the regions of the phase diagram that involve CH4-hydrates. The resulting simulator (hereafter referred to as the JFTS+H code) can describe all possible scenarios of hydrate occurrence, dissociation and formation/evolution and is to be used for the investigation of problems of (a) gas production from natural CH4-hydrate accumulations in geologic media, as well as for (b) the analysis of any laboratory experiments involving CH4-hydrates. As indicated by the JFTS name, this simulator is written in the Julia programming language and its parallelization is based on the Message Passing Interface (MPI) approach. The JFTS+H simulator is a fully-implicit, Jacobian-based compositional simulator that describes the accumulation, flow and transport of heat, and up to four mass components (H2O, CH4, CH4-hydrate and a water-soluble inhibitor) distributed among four possible phases (aqueous, gas, hydrate, and ice) in complex 3D geologic systems. The dissociation and formation of CH4-hydrates can be described using either an equilibrium or a kinetic model. The automatic derivate capability of Julia greatly simplifies and enhances the Jacobian computations. The MPI Interface (Blaise, 2019) is implemented in all components of the code, and the METIS library (Karypis, 2013) is used for the domain decomposition needed for the effective parallelization of the solution of the Jacobian matrix equation that is accomplished using the LIS library (Nishida, 2010) of parallel Conjugate Gradient solvers for large systems of simultaneous linear equations. The JFTS+H code can model the fluid flow, thermal and geochemical processes associated with the formation and dissociation of CH4-hydrates in geological media, either in laboratory or in natural hydrate accumulations. This code can simulate any combination of the three possible gas hydrate dissociation methods (depressurization, thermal stimulation, and inhibitor effects), and computes all associated parameters describing the system behavior. The JFTS+H results show very good agreement with solutions of standard reference problems, and of large 2D and 3D problems obtained from another well-established and widely used numerical simulator. The code exploits the speed, computational efficiency and low memory requirements of the Julia programming language. The parallel architecture of JFTS+H addresses the persistent problem of very large computational demands in serial hydrate simulations by using multiple processors to reduce the overall execution time and achieve scalable speedups. The code minimizes communications between processors and maximizes computations within the same computational node, which has important consequences (especially when coupled with the automatic derivative capabilities of Julia) on performance in the development of the Jacobian matrix. An optimal LIS solver is recommended for this type of problem after evaluating different options. This approach provides both speedup and computational efficiency results when different numbers of processors are called in the solution process. This work is believed to be the first application of Julia (a new, highly efficient language designed for demanding scientific computations) to create a simulator for flow and transport in porous media. JFTS+H is a fast, robust parallel simulator that uses the most recent scientific advances to account for all known processes in a dynamic hydrate system and works seamlessly on any computational platform (from laptop computers to workstations, to clusters and supercomputers with thousands of processors).

The work described in this paper develops a methodology for modelling and analysis of complex timed systems. The methodology is based on the Stochastic Reward Nets (SRN) [1]-[4] formalism, which has gained its popularity by its ability to enable the studying of the performability, reliability and availability of, e.g., computer and communication systems. SRN is an extension of Generalized Stochastic Petri Nets (GSPN) and it is supported by such tools as the Stochastic Petri Net Package (SPNP) [5]-[6]. Power and accuracy in the application of SRN derive from mapping a model into a corresponding Markov Reward Model (MRM) from which quantitative measures are extracted in terms of reward functions associated to tangible markings of the source model. To cope with large models which cause state explosions in the underlying MRM, simulations are used [2].

In this paper the FDS 6 code ability to simulate the airflows generated by jet fans in a real road tunnel is studied. A transient model of the 898 m long bi-directional highway Polana tunnel is cre...

In this paper, an endeavor has been made to fit three distributions Marshall–Olkin with exponential distributions, Marshall–Olkin with exponentiated exponential distributions and Marshall–Olkin with exponentiated extension distribution keeping in mind the end goal to actualize Bayesian techniques to examine visualization of prognosis of women with breast cancer and demonstrate through utilizing Stan. Stan is an abnormal model dialect for Bayesian displaying and deduction. This model applies to a genuine survival controlled information with the goal that every one of the ideas and calculations will be around similar information. Stan code has been created and enhanced to actualize a censored system all through utilizing Stan technique. Moreover, parallel simulation tools are also implemented and additionally actualized with a broad utilization of rstan.

This work is devoted to evaluating the performance of a multicore CPU Elbrus-8C processor in supercomputer computational fluid dynamics (CFD) applications. Parallel simulation codes based on highly accurate methods on unstructured meshes for modeling the turbulent flows are considered. The main features of the Elbrus architecture are described, and the approaches for adaptating and optimizing the computing software are presented. The performance is investigated for both entire algorithms and their operations separately. The results of comparative testing with different multicore Intel and AMD CPUs are presented.

The continuous growth of ore train lengths demands more efficient schedules, improved transit estimations and accident prevention schemes. Braking is a key component in achieving these objectives. ...

Given the non-repeatability, complexity, and unpredictability of unconventional public health emergencies, building accurate models and making effective response decisions based only on traditional prediction–response decision-making methods are difficult. To solve this problem, under the scenario–response paradigm and theories on parallel emergency management and discrete event system (DES), the parallel simulation decision-making framework (PSDF), which includes the methods of abstract modeling, simulation operation, decision-making optimization, and parallel control, is proposed for unconventional public health emergency response processes. Furthermore, with the example of the severe acute respiratory syndrome (SARS) response process, the evolutionary scenarios that include infected patients and diagnostic processes are transformed into simulation processes. Then, the validity and operability of the DES–PSDF method proposed in this paper are verified by the results of a simulation experiment. The results demonstrated that, in the case of insufficient prior knowledge, effective parallel simulation models can be constructed and improved dynamically by multi-stage parallel controlling. Public health system bottlenecks and relevant effective response solutions can also be obtained by iterative simulation and optimizing decisions. To meet the urgent requirements of emergency response, the DES–PSDF method introduces a new response decision-making concept for unconventional public health emergencies.

In this article, we present experiences implementing a general Parallel Discrete Event Simulation (PDES) accelerator on a Field Programmable Gate Array (FPGA). The accelerator can be specialized to any particular simulation model by defining the object states and the event handling code, which are then synthesized into a custom accelerator for the given model. The accelerator consists of several event processors that can process events in parallel while maintaining the dependencies between them. Events are automatically sorted by a self-sorting event queue. The accelerator supports optimistic simulation by automatically keeping track of event history and supporting rollbacks. The architecture is limited in scalability locally by the communication and port bandwidth of the different structures. However, it is designed to allow multiple accelerators to be connected to scale up the simulation. We evaluate the design and explore several design trade-offs and optimizations. We show that the accelerator can scale to 64 concurrent event processors relative to the performance of a single event processor. At this point, the scalability becomes limited by contention on the shared structures within the datapath. To alleviate this bottleneck, we also develop a new version of the datapath that partitions the state and event space of the simulation but allows these partitions to share the use of the event processors. The new design substantially reduces contention and improves the performance with 64 processors from 49x to 62x relative to a single processor design. We went through two iterations of the design of PDES-A, first using Verilog and then using Chisel (for the partitioned version of the design). We report in this article on some observations in the differences in prototyping accelerators using these two different languages. PDES-A outperforms the ROSS simulator running on a 12-core Intel Xeon machine by a factor of 3.2x with less than 15% of the power consumption. Our future work includes building multiple interconnected PDES-A cores.

The article considers vector computation methods (bit-parallel simulation) for determining the observability of combinational logic gates. The computations produce an ODC (observability don’t care) set of all gates for a given set of circuit states. These results make it possible to evaluate the probability of logical masking of a random circuit fault. The methods are compared by accuracy and time costs using testing results for ISCAS ’85 benchmark circuits.

Computer simulations are widely used to design and evaluate air traffic systems. A fast time simulation capability is essential to effectively explore the consequences of decisions in airspace design, air traffic management, and operations. A parallel simulation approach is proposed to accelerate fast time simulation of air traffic networks that exploits both temporal and spatial parallelisms. A time-parallel algorithm is first described that simulates different time intervals concurrently and uses a fix up computation that exploits the scheduled nature of commercial air traffic to address the problem of dependencies between time segments. The time-parallel algorithm is then extended with a space-parallel simulation approach using Time Warp to simulate each time segment in parallel thereby increasing the amount of parallelism that can be exploited. The time and space-parallel algorithms are evaluated using a simulation of the U.S. National Airspace System (NAS). Experimental data is presented demonstrating that this approach can achieve greater acceleration than what can be achieved by exploiting time-parallel or space-parallel simulation techniques alone.

The heat and moisture transfer performance in clothed human body affects human life quality (e.g., comfort and health) directly. Accurate modeling and highly efficient simulation of the heat and moisture transfer mechanisms in clothed human body is helpful to enhance the human life quality. In this paper, we first describe a heat and moisture transfer simulation model of clothed human body, which comprises the George Fu’s human thermal physiological model and a 3D heat and moisture transfer model in clothing, and the thermoregulation behaviors as well as the heat transfer mechanisms are taken into consideration. Then according to the physiological and geometrical features of human body, a parallel algorithm for the heat and moisture transfer simulation in clothed human body is proposed. The SPMD framework has been utilized for data parallel. At last, case studies with different environment scenes are presented. The visual simulated results are displayed, and the parallel performance is discussed.

Thermal crosstalk in a highly integrated RRAM array due to the self-heating effect is one of the most critical issues affecting device reliability. In this paper, two types of “thermal-house” structures are proposed to optimize the thermal management of the RRAM array. An in-house developed parallel simulator is employed to study the performance of the proposed thermal house structures in terms of resistance ratio and crosstalk temperature. It is demonstrated that the proposed thermal house structures can help to reduce thermal crosstalk in high-density RRAM arrays. Some suggestions are also provided for further improving the thermal management capability of the thermal houses as well.

In order to solve the problem that the complicated and changeable modern warfare makes the commander's decision-making difficult, this paper studied dynamic generation method of simulation entities in parallel simulation system. First, a parallel simulation entity model classification system was established, and a simulation entity description specification system was constructed; then, the process of simulation entities dynamic generation was analyzed, and a dynamic matching algorithm for unknown target simulation models based on KNN was studied. The historical tracks were used to construct a test set and the algorithm validity test is performed. The test results show the effectiveness of the algorithm, which can provide technical support for generating the parallel simulation of actual scenarios.

Urban traffic simulation of extensive areas with complex driver models poses a significant computational challenge. Developing highly scalable parallel simulation algorithms is the only feasible way to provide useful results in this case. In this paper, we present extensions of the SMARTS system, a traffic simulation tool, which provides efficient scalability with a large number of parallel processes. The presented extensions enabled its scalability for HPC-grade systems. The extended version has been thoroughly tested in strong and weak scalability scenarios for up to 2400 computing cores of a supercomputer. The satisfactory scalability has been achieved by introducing several significant improvements, which have been discussed in details.

Detailed models of numerous groups of social beings, which find applications in broad range of applications, require efficient methods of parallel simulation. Detailed features of particular models strongly influence the complexity of the parallelization problem. In this paper we identify and analyze existing classes of models and possible approaches to their simulation parallelization. We propose a new method for efficient scalability of the most challenging class of models: stochastic, with beings mobility and mutual exclusion of actions. The method is based on a concept of two-stage application of plans, which ensures equivalence of parallel and sequential execution. The method is analyzed in terms of distribution transparency and scalability at HPC-grade hardware. Both weak and strong scalability tests show speedup close to linear with more than 3000 parallel workers.

Cheap parallel computing has greatly extended the reach of ranking & selection (R&S) for simulation optimization. In this paper we present an evaluation of bi-PASS, a R&S procedure created specifically for parallel implementation and very large numbers of system designs. We compare bi-PASS to the state-of-the-art Good Selection Procedure and an easy-to-implement subset selection procedure. This is one of the few papers to consider both computational and statistical comparison of parallel R&S procedures.

In this work, an in-house developed parallel-computation simulator is employed to study the electrothermal performance of resistive random access memory (RRAM). To save computing storage, the 3D hexahedral elements are used to discretize the structures. The validity of the in-house simulator is investigated first, and then the thermal crosstalk effect of RRAM array is studied base on simulation results.

The paper presents results from implementation of parallel simulation of a model of layer of retina ganglion cells. The aim was to decrease computational time since this layer appeared to be the bottleneck in the developed hierarchical model of human visual system. Each retina ganglion cell was modelled by a spatio-temporal filter convolved with visual scene observed by the eyes so its computational time was crucial to overall simulation. Our parallel implementation that distributes pieces of the layer to the several independently working processors decreased significantly the computational time.

The IEEE SystemC language is widely used in industry and academia to model and simulate system-level designs. Despite the availability of multi- and many-core host processors, however, the Accellera reference simulator is still based on sequential discrete event simulation, utilizing only a single core at any time. While many advanced parallel simulation approaches have been proposed, most require modification of the SystemC source code so that the model is free from parallel access conflicts and rely on the designer to manually perform this difficult transformation.

Quantum coherence allows for reduced-memory simulators of classical processes. Using recent results in single-shot quantum thermodynamics, we derive a minimal work cost rate for quantum simulators that is quasistatically attainable in the limit of asymptotically-infinite parallel simulation. Comparing this cost with the classical regime reveals that quantizing classical simulators not only results in memory compression but also in reduced dissipation. We explore this advantage across a suite of representative examples., Comment: 7 pages, 3 figures; Supplementary material: 8 pages, 1 figure; http://csc.ucdavis.edu/~cmg/compmech/pubs/qmcate.htm

Automotive applications are driving the need for a systematic way to decrease analog test escape rates to 0 DPPM, while providing functional safety. This tutorial briefly reviews the history of analog fault simulation, from academic simulation of basic shorts and opens, to the advent of industrial analog defect/fault simulators. Then it addresses the two biggest problems: no industry-accepted fault model, and impractically long simulation time. The solutions are the proposed IEEE P2427 standard for analog defect coverage, for which a brief summary of its requirements is provided, and a variety of methods to reduce total simulation time, such as defect collapsing, simulating only the most likely defects or likelihood-weighted randomly selection of defects, and parallel simulation.

In the current report, we present further developments of a unified open-access Monte Carlo (MC) based computational tool for simulation of twisted light propagation in turbid tissue-like scattering medium. We introduce an online browser-based application and a media model which considers both spatial and volumetric variations such surface roughness and subsurface scattering optical properties. The online application has been integrated with the parallel simulation framework developed in-house and is being extensively used in the ongoing studies of twisted light propagation in turbid media (e.g. phantoms and cancerous lesions). Rigorous validation against data obtained during experimental studies is presented.

The digital transformation journey provides new opportunities for running simulations through cloud computing, with flexibility in hardware resources and availability of a wide array of software tools that can enhance decision-making. This work reviews the benefits of running reservoir simulations in a cloud environment and demonstrates the efficiency and cost savings. Additionally, a workflow for uncertainty analysis and history matching that integrates data analysis and machine-learning tools is presented. First, the hardware architecture must be designed to meet parallel reservoir simulation needs: significant message passing occurs between computer nodes, and for satisfactory performance, these nodes must be connected by a low-latency network, rather than be randomly located. Second, to ensure portability and easy replication across multiple cloud sites and platforms, the software performing the simulations must be containerized. Third, to reduce the time required to start a new simulation run, the Kubernetes platform is used to optimize resource allocation. Finally, reservoir simulation in the cloud is no longer merely the running of the simulation model, but it is integrated with data management and data analysis tools for decision-making. The cloud-based simulation services discussed herein exhibit good results during scale up, when a simulation operation requires a larger number of central processing units and/or greater memory, and also during scale out, when thousands of operation scenarios are necessary for history matching. The "pay as you go" pricing model reduces the time and capital costs of acquiring the new computing infrastructure to nearly zero, and the effectively unlimited scale-out capability can reduce the elapsed time for history matching by 80%. The availability of data centers in different regions is good for team collaborations. It serves the data management tool well to track history data, perform data mining, extract more information, and make decisions. Compared to traditional reservoir simulation, the cloud-based reservoir simulation software as a service model simplifies the process and reduces hardware acquisition and maintenance costs. Integrating intelligent data analysis with simulation helps quantify the uncertainty in the model and enables improved decisions.

Population Dynamics P systems is a modelling framework that have been used successfully for some important real ecosystems. This model is inherently probabilistic, and the scheme of rules is very exible, allowing even cooperation between membranes. Thus, its simulation has been a challenge in the past years, leading to several simulation algorithms. The latest one, which has been proved to be the most accurate so far, is DCBA. The main drawback of DCBA is its complexity, requiring a very large table to handle all competitions. In this paper, we discuss two strategies to decrease this table, allowing a more lightweight version of DCBA that can be used in parallel implementations. Ministerio de Economía, Industria y Competitividad TIN2017-89842-P (MABICAP)

The methods known collectively as “ranking & selection” have been a theoretical and practical success story for the optimization of simulated stochastic systems: they are widely used in practice, have been implemented in commercial simulation software, and research has made them more and more statistically efficient. However, “statistically efficient” has meant minimizing the number of simulation-generated observations required to make a selection, or maximizing the strength of the inference given a budget of observations. Exploiting high-performance computing, and specifically the capability to simulate many feasible solutions in parallel, has challenged the ranking & selection paradigm. In this paper we review the challenge and suggest an entirely different approach.

Improving space situational awareness (SSA) remains one of the Department of Defense’s (DoD) top priorities. Current research has shown that the modeling of geosynchronous orbit (GEO) SSA architectures can help identify optimal combinations of ground- and space-based sensors. This paper extends previous research by expanding design boundaries and refining the methodology. A multi-objective genetic algorithm was used to examine this increased trade-space containing 1022 possible design combinations. The results of the optimizer clearly favor 1.0 m aperture ground telescopes combined with 0.15 m aperture sensors in a 12-satellite geosynchronous polar orbit (GPO) constellation. The GPO regime offers increased access to GEO resident space objects (RSO) since other orbits are restricted by a 40° solar exclusion angle. When performance is held constant, a GPO satellite constellation offers a 22.4% reduction in total system cost when compared to Sun synchronous orbit (SSO), equatorial low earth orbit (LEO), and near-GEO constellations. Parallel high-performance computing provides the possibility of solving an entirely new class of complex problems of interest to the DoD. The results of this research can educate national policy makers on the benefits of proposed upgrades to current and future SSA systems.

We consider a wireless sensor network (WSN) in the form of a chain of sensors with several sinks. Chiasserini–Garetto conditions are imposed on the functioning of the network nodes and the transmission environment. The number of network nodes is assumed in the thousands. A parallel simulation model is constructed to estimate the WSN performance parameters. Computer experiments conducted on a BlueGene/P supercomputer show good scalability of the model.

The hydraulic verification of combined sewer systems as well as the assessment of combined sewer overflows (CSOs) can be conducted using a hydrodynamic model. Unfortunately, long-term simulations with hydrodynamic models for the assessment of CSOs can cause unacceptably long computation times. Using only a series of storm events instead of a precipitation continuum can reduce this time and enables parallel simulation of single storm events. We introduce a method to select this series of storm events. The method’s parameters have been optimized to replicate the overflow volume of the continuous simulation and to minimize the overall computation time. This optimization revealed a generally applicable parameter set that results in series of storm events that are shorter than the precipitation continuum by 86.2–95.2% for the investigated cases. Additionally, the deviation of overflow volume between continuous simulation and series simulation ranges between only 0.1% and 4.1%.

Aiming at the problems of easy fault diagnosis and difficult early warning of mine hoist, a parallel system architecture of hoist fault early warning based on big data is proposed, the structure of each subsystem of hoist is analyzed, and a parallel simulation system of hoist fault early warning is established; secondly, the Hadoop ecosystem of hoist is established on the virtual machine, and the massive data is mined by using clustering algorithm and association rule algorithm, so as to speed up the calculation speed and improve the reliability of early warning; finally, the safety state evaluation rules of hoist are proposed, and the system decision is made according to the fault early warning results. The experimental results show that it can achieve the purpose of fault prediction.

In order to solve the problems of the traditional GNSS multipath signal simulation methods, such as the complexity increases linearly with the number of multipath signals, inconvenient parameter updating and long operation time, a GPU based GNSS multipath signal parallel simulation method is proposed. Based on Farrow variable fractional delay filter, an independent parallel computing model of multi-channel filter coefficients is established, and a large number of floating-point units in GPU are used for parallel computing and filtering. Aiming at the performance bottleneck of this method, the optimization strategy of asynchronous parallel execution is given. The computer simulation results show that the complexity and operation time of the proposed method will not increase with the increase of the number of multipath signals. For the GNSS direct signal with sampling rate of 75MHz and time length of 1s, the maximum time consuming of the proposed method to generate 50 ∼ 1000 multipath signals is 158.6ms. Compared with the method of serial simulation on CPU, the proposed method speeds up to about 9.5 times, and the real-time simulation of multipath signals in complex environment can be realized.

Closed-loop insulin delivery system, also known as artificial pancreas (AP), provides the blood glucose control in diabetic patients, enabling the automatic blood-sugar management and reducing the risks and improving the lives of people with diabetes. A new three-compartmental model of glucose-insulin interaction for AP is presented and tested in this paper. The glucose and insulin "spaces" are split into a plasma compartment and interstitial fluids compartment, respectively. The model includes an additional subcutaneous compartment and provides three explicit delays and three parameters influencing the regulatory system and correlating with the physiopathology of the patients. Two delays are related with hepatic glucose production and insulin secretion; the third delay represents the lag time in the absorption of exogenous insulin in subcutaneous tissue. The parameters regulate the system dynamics acting on the glucose utilization and the insulin secretion. The clinical data (including information on food ingestion and exogenous insulin injection) from five case studies of Type 1 diabetics are presented and used to validate the mathematical model. After training the parameters for each case study, the model well simulates the glucose level during a 4-day test. The estimated values are physiologically meaningful and provide a further insight on the subject's dysfunctions and on the state of the disease. The results have been also compared with a parallel simulation carried out by implementing a previous two-compartmental model. The proposed algorithm produces a lower sum of the squared error between the simulated and the measured glucose concentrations over time.

A parallel simulation of the gas-solid motions in a 3-D full-loop dual-side refeed circulating fluidized bed (DRCFB) is carried out by using Large-eddy Simulation coupled with Discrete Element Method (LES-DEM), in which the gas and the solid motions are solved under the Eulerian and the Lagrangian frames, respectively. The start-up flow patterns, the time-related solid phase properties about solid cycle time and solid residence time (SRT) distributions, and the improvements of gas-solid flow uniformity are explored. Furthermore, the influences of different operating conditions on the time-related solid phase properties are discussed. The results demonstrate that the transient pressure drop is a criterion for determining steady state in the start-up process and the fluctuations under different superficial velocities differ. The solid cycle time and the SRT distribution curves show a feature of early peak with an extended tail, which indicates that the solid flow exhibits a back-mixing phenomenon. The averaged solid cycle time in the whole system and the averaged SRTs in the three components ( i.e. , riser, cyclone, and dipleg) show distinct characteristics under different operating conditions. Moreover, nearly 70% of the solid cycle time elapses in the riser and 25% of that elapses in the dipleg while only 5% of that elapses in the cyclone. Finally, the dual-side refeed structure remarkably improve the gas-solid flow uniformity ( i.e. , homogenous) in the DRCFB riser, especially in the inlet and outlet regions.

Em arquitetura de computadores, o uso de simuladores é predominante em todos os grupos de pesquisa, com uma ampla variedade de abordagens e implementações.No entanto, falta na literatura uma análise detalhada de simuladores de arquiteturas paralelas que suportem workloads de Computação de Alto Desempenho (High Performance Computing - HPC). Este trabalho busca analisar o impacto do prefetcher na precisão da simulação paralela realizada pelo ZSim, um simulador de arquiteturas paralelas. Observamos que, devido à falta de modelagem de prefetcher, as estatı́sticas da hierarquia de memória apresentam comportamentos imprecisos, com erros de até 2.600%.

A multi-branch parallel simulation method and an architecture of application system are proposed in this paper based on symbiotic potential, and method of construction and calibration of parallel battlefield based on real data, as well as generation of simulation branch based on situation interpretation etc. are proposed. Fast building and adjustment of situation of real time simulation are realized based on simulation to meet the requirements of consistency and parallel operation between virtual simulation and real systems. Multibranch operation management, multi-branch highperformance operation support and other methods are proposed to support the dynamic generation of massive parallel simulation copies based on real-time intelligence and ultra-realtime and large-sample operation to meet the requirements of advanced evaluation of real-time situation. At the same time, a set of simulation application verification frameworks for typical task situation is presented to support the construction of multibranch simulation operation environment, and provide technical verification means for real-time situation prediction and evaluation.